Update README.md

README.md

@@ -1,23 +1,30 @@
+---
+language: en
+tags:
+  - sql
+  - code-generation
+  - reinforcement-learning
+  - text-generation
+datasets:
+  - spider
+
+---
+
 # Model Card for RL-GRPO-SQL-Model
 
 ## Model Details
 
 ### Model Description
-- **Model type**: Fine-tuned Model with RL
-- **Training approach**: Reinforcement Learning with GRPO
-- **Task**: SQL generation/understanding
+- **Model type**: Fine-tuned Causal Language Model with Reinforcement Learning
+- **Training approach**: Reinforcement Learning with GRPO (Group Relative Policy Optimization)
+- **Task**: SQL generation and understanding
 - **Developed by**: Ali Assi
 
 ## Training Data
 
 - **Data sources**: Spider train set
-- **Preprocessing**: parsing and validation
-
-## Model Performance
-
-### Benchmarks
-
-Spider test set
+- **Preprocessing**: Parsing and validation
+- **Languages**: English
 
 ## How to Use
 
@@ -26,4 +33,30 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 
 tokenizer = AutoTokenizer.from_pretrained("ALI-USER/rl-grpo-sql-model")
 model = AutoModelForCausalLM.from_pretrained("ALI-USER/rl-grpo-sql-model")
-```
+
+# Example usage
+prompt = "Generate SQL for: Find all customers with orders over $100"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=512)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Limitations
+
+- Model performance may vary depending on database schema complexity
+
+## Ethical Considerations
+
+- May generate SQL queries that are inefficient or unsafe if not properly validated
+- Should be used with query validation before execution
+
+## Intended Uses
+
+**Primary use cases:**
+- Natural language to SQL translation
+- SQL code generation assistance
+- Educational purposes for SQL understanding
+
+**Out-of-scope uses:**
+- Direct production deployment without query validation
+- Non-English language queries (not trained for this)